bcs_consultingfandomcom-20200215-history
Hey
Age and Gender Differences on Achievement Among Students with Special Learning Needs Cedric B. Stewart Sam Houston State University Age and Gender Differences on Achievement Among Students with Special Learning Needs Research Questions '' The following research questions were addressed in this study: (a) what is the difference in Performance IQ scores as a function of disability group membership and age groupings among students with special learning needs ?, and (b) what is the difference in Arithmetic skills as a function of disability group membership and gender among students with special learning needs? Results A review of the histograms with normal curves did not suggest any significant departures from normality. The standardized skewness coefficients (i.e., skewness divided by the standardized error of skewness) for both research questions ranged between -1.77 and 4.50. In addition, the standardized kurtosis coefficients (i.e., kurtosis divided by the standard error of kurtosis) ranged between -1.68 and 2.79. Whereas, only one skewness coefficient was outside the bounds of normality, -3.00 and 3.00, overall the standardized coefficients of the data were within the accepted range of normality (Onwuegbuzie & Daniel, 2002). Based on this normality, the use of a parametric factorial analysis of variance (ANOVA) was justified. For research question one, a 3 (disability group membership) x 4 (recoded age grouping) ANOVA was conducted to study (a) the effects of Performance IQ and age; (b) how Performance IQ is related to disability group membership; and, © the interaction of age and disability group membership in regards to Performance IQ. Furthermore, research question two utilized a 2 (gender) x 3 (disability group membership) ANOVA to examine (a) gender differences in Arithmetic scores; (b) differences in Arithmetic scores based on disability group membership; and © the interaction of gender and disability group membership as they relate to Arithmetic skills. A Bonferroni adjustment was utilized due to the multiple research questions addressed in an effort to determine if statistical significance was evident. It was computed by taking the normal alpha level, .05, and dividing by 2 (i.e., .05/2 = .025). Therefore, for a result to be statistically significant, the adjusted alpha level must be at or below .025. The ANOVA for research question one revealed that there was no statistically significant interaction between disability group membership and age grouping, ''F(6, 1126) = 1.46, p'' > .025. Both main effects, however, did indicate statistical significance. For recoded age groupings, the main effect was, ''F(2, 1126) = 382.93, p'' < .025, with a partial eta of .01, indicating a small effect size (Cohen, 1988) . The main effect for disability grouping was, ''F(3, 1126) = 4.03, p'' < .025, with a large associated effect size of .41 (ƞ'' 2 = .41). Descriptive statistics pertaining to Performance IQ as a function of both disability group membership and recoded age groupings are located in Table 1. --------------------------------------------- Insert Table 1 about here --------------------------------------------- Research question two indicated statistically significant interaction between gender and disability group membership, F''(2, 1130) = 4.99, ''p < .025. The associated effect size of this difference as measured by ƞ ''2'', was .01. Using Cohen’s (1988) criteria, this coefficient indicated a small effect size. Regardless of disability group membership, gender discrepancies were consistently present for the three disability groupings with boys outperforming girls. The most significant difference between genders in Arithmetic skills, however, occurred in the group of students that were tested but did not qualify. Equally important, both main effects also indicated statistical significance. For gender, the main effect was, F''(1, 1130) = 39.43, ''p ''< .025. In addition, for disability grouping the main effect was, ''F(2, 1130) = 231.98, p ''< .025. Using Cohen’s (1988) criteria, respective effect sizes were small (ƞ 2'' = .03) and moderate (ƞ 2 = .30). The students with Learning Disabilities performed better than any other subgroup. The students with Mental Retardation, however, did not perform as well as students that were previously tested but did not qualify. Table 2 presents descriptive statistics pertaining to Arithmetic skills as a function of gender and disability grouping. --------------------------------------------- Insert Table 2 about here --------------------------------------------- References Cohen, J. (1988). Statistical power analysis for the behavioral sciences ''(2nd ed.).'' Hillsdale, NJ: Lawrence Erlbaum. Onwuegbuzie, A. J., & Daniel, L. G. (2002). Uses and misuses of the correlation coefficient. Research in the Schools, 9(1), 73-90. Table 1 ''Means and Standard Deviations for Performance IQ as a Function of Age and Disability '' Table 2 ''Descriptive Statistics for Arithmetic Skills as a Function of Gender and Disability Group Membership '' Appendix SPSS Statistical Output RQ 1 F(2, 1126) = 382.93, p < .05 recode age effect size = .011, small effect size F(3, 1126) = 4.03, p < .05 group effect size = .405, large effect size F(6, 1126) = 1.46, p > .05 recodeage & group = .008, small effect size RQ 2 F(2, 1130) = 231.98, p < .05 group effect size .291 = Moderate effect size F(1, 1130) = 39.43, p < .05 gender effect size .034 = Small effect size F (2, 1130) = 4.99, p < .05 group and gender .009 = Small effect size